Leveraging artificial intelligence to advance the understanding of chemical neurotoxicity

Michael Aschner, Robin Mesnage, Anca Oana Docea, Monica Maria Bastos Paoliello, Aristides Tsatsakis, Georgios Giannakakis, Georgios Z. Papadakis, Silvio Roberto Vinceti, Abel Santamaria, Anatoly V. Skalny, Alexey A. Tinkov

Research output: Contribution to journalComment/debatepeer-review

Abstract

Neurotoxicology is a specialty that aims to understand and explain the impact of chemicals, xenobiotics and physical conditions on nervous system function throughout the life span. Herein, we point to the need for integration of novel translational bioinformatics and chemo-informatics approaches, such as machine learning (ML) and artificial intelligence (AI) to the discipline. Specifically, we advance the notion that AI and ML will be helpful in identifying neurotoxic signatures, provide reliable data in predicting neurotoxicity in the context of genetic variability, and improve the understanding of neurotoxic outcomes associated with exposures to mixtures, to name a few.

Original languageEnglish (US)
Pages (from-to)9-11
Number of pages3
JournalNeurotoxicology
Volume89
DOIs
StatePublished - Mar 2022

Keywords

  • Artificial intelligence
  • Commentary
  • Neurotoxicity

ASJC Scopus subject areas

  • Neuroscience(all)
  • Toxicology

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